PromptGuard is a firewall designed specifically for AI applications, addressing security risks such as prompt injection, data leaks, and multi-turn attacks. Below are 13 security & compliance platforms apps with similar functionality to PromptGuard, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
PromptLock is a web-based security platform that acts as a firewall for AI systems, blocking prompt injection attacks, preventing data leaks, and ensuring compliance with regulations like HIPAA and GDPR. It is aimed at developers and organizations deploying AI applications that require robust security.
SafePrompt is an API service that detects and blocks prompt injection attacks in AI-powered applications. It provides fast, accurate validation of user inputs, integrates easily via API or Chrome extension, and is designed for developers building secure AI apps.
Strategic Prompt Architect addresses security risks associated with AI systems by offering tools designed to detect prompt injection attacks, prevent credential leaks, and scan for malicious instructions hidden in files. The platform is intended for a range of users, including individuals, developers, professionals, and enterprises, each facing unique challenges as AI becomes increasingly integrated into daily workflows. The service provides two main products. MalPromptSentinel is a free browser extension that enables real-time scanning for prompt injection and credential leaks within AI chat interfaces. It operates entirely locally, ensuring that user data remains within the browser and is not transmitted externally. The extension can also scan Claude Code skill files and is positioned as a privacy-first solution for individuals and professionals who interact with AI assistants or handle potentially risky content from external sources. For developers and organizations requiring programmatic and scalable solutions, Strategic Prompt Architect offers the MPS-Agentic Cloud API. This cloud-based RESTful API facilitates automated scanning of prompts and files in production environments, supporting both file and batch processing. Additional features include scan history with SHA-256 verification, rate limiting, and usage analytics. This API is designed to be integrated at points where external content enters applications or agentic workflows, providing a layer of defense against malicious inputs before they reach AI systems. Pricing for the MPS-Agentic Cloud API is structured across several tiers: Starter ($10/month for 1,000 scans), Builder ($29/month for 10,000 scans), Professional ($129/month for 50,000 scans), and Enterprise plans ($1,000/month for 250,000 scans with 5 seats, and $2,000/month for 500,000 scans with 10 seats). MalPromptSentinel, the browser extension, is available for free. Strategic Prompt Architect positions itself as an AI security toolset focused on prompt injection detection, credential leak prevention, and malicious content scanning, catering to both individual users and organizations seeking to secure their AI workflows.
PasteGuard is an open-source privacy layer designed to mask sensitive information before it is sent to AI models such as ChatGPT, Claude, Gemini, and coding agents. It addresses the challenge of protecting private data—including names, emails, secrets, customer details, and a wide range of credentials—when interacting with AI providers or integrating AI into applications. By replacing sensitive elements with placeholders, PasteGuard ensures that the context required for AI processing is preserved while the original data remains confidential and is not exposed to external providers. The tool detects and masks over 30 types of private data and secrets in any language, including names, emails, phone numbers, credit card numbers, IBANs, EU VAT numbers, IP addresses, locations, API keys, SSH keys, JWT tokens, passwords, connection strings, private keys, and bearer tokens. PasteGuard operates by intercepting user input before it reaches the AI provider, substituting sensitive information with standardized placeholders (such as [[PERSON_1]], [[EMAIL_1]], or [[API_KEY_1]]). Where supported, it can also restore the original values in AI responses for the user’s convenience. PasteGuard is suitable for teams and organizations with strict privacy requirements, such as those needing to comply with GDPR, DORA, client confidentiality agreements, or internal AI usage policies. It is particularly useful for scenarios where raw customer data, client files, or secrets cannot be shared with AI services. The platform can be used locally, self-hosted in a team’s own environment, or integrated in front of apps and SDKs to mask data before it reaches APIs from providers like OpenAI and Anthropic. Delivery options include a browser extension—currently in beta—for ChatGPT, Claude, and Gemini, as well as Docker-based self-hosting for integration with OpenAI-compatible apps, SDKs, and coding agents. PasteGuard is fully open-source, auditable, and does not include telemetry or tracking. 0 license, allowing teams to deploy and audit the tool within their own compliance boundaries.
AgentGuard is a runtime governance platform designed for production AI agents, with a focus on meeting regulatory and compliance requirements in financial services, particularly for APRA-regulated organizations in Australia and the Asia-Pacific region. The tool provides operational controls and audit evidence aligned with frameworks such as APRA CPS 230, the EU AI Act, and ISO 42001, enabling organizations to deploy AI agents that their regulators can approve. A central feature of AgentGuard is its runtime enforcement: it operates within the agent execution environment, intercepting tool calls, model outputs, and spending actions before they occur. Policy enforcement is managed through YAML-based declarative policies, allowing organizations to define tool whitelists, daily spending limits, requirements for human approval, and operational rules such as after-hours restrictions. The platform generates signed, Bitcoin-anchored audit records for every agent decision, and compiles these into compliance packs in PDF format, mapped to regulatory frameworks and suitable for board and auditor review. AgentGuard integrates with multiple AI agent frameworks, including OpenClaw, LangChain, CrewAI, AutoGen, OpenAI Assistants, and MCP. js with a single decorator or middleware. For OpenClaw, AgentGuard provides native governance features such as per-agent policy, fleet-level monitoring, cost tracking, and a killswitch for policy breaches, all without requiring code forks or patches. The platform can be installed locally or behind an organization's firewall, with no dependency on a SaaS runtime. The service is available under several pricing tiers: a free plan for one agent with limited retention and an MIT-licensed SDK; a Team plan at $499 AUD per month for up to 25 agents and extended retention with additional support; and a Compliance plan at $2,500 AUD per month, offering unlimited agents, extended retention, compliance evidence packs, and Bitcoin-anchored audit roots. An enterprise option with on-premises deployment and dedicated support is also available. AgentGuard is developed by The Bot Club Pty Ltd.
AI DLP & Prompt Management for Teams is a platform designed to help organizations secure and manage their use of AI tools such as ChatGPT, Claude, Gemini, Copilot, and Perplexity. It addresses the challenge of protecting sensitive data and ensuring compliance when teams interact with AI systems, offering a unified solution for data loss prevention, prompt governance, and audit readiness. The platform provides two layers of protection. The first is network-level control, which allows administrators to approve specific AI tools for use and block unapproved ones at the DNS level using Cloudflare Gateway. This approach covers every device on the network, including browsers, native applications, mobile devices, and CLI tools, and displays a clear block page to users when access is denied. The second layer is content-level DLP, which scans every prompt sent to approved AI tools in real time within the browser. This scanning can detect and block sensitive information such as PII, credentials, API keys, and patient data, using over 40 detection rules and 20 compliance packs including HIPAA, SOC 2, PCI-DSS, and GDPR. The system can block, warn, or automatically redact sensitive data before it reaches the AI tool, all via a browser extension that installs quickly without the need for a proxy. Additional features include Shadow AI Discovery, which monitors and reports on AI tool usage across departments, roles, individuals, and devices. The Shared Prompt Library provides a searchable repository of approved prompts, complete with templates, approval workflows, quality guidelines, and usage analytics. The platform also offers a comprehensive audit and compliance dashboard with Sankey flow diagrams, violation heatmaps, risk scoring, compliance coverage, and CSV export options for auditors. Real-time DLP scanning and prompt governance are integrated into a single interface, streamlining security and compliance workflows. AI DLP & Prompt Management for Teams is delivered primarily through a browser extension and an admin dashboard, with network-level controls powered by Cloudflare Zero Trust. The service is free for up to 3 members for workspace setup and up to 50 users for DNS-level blocking. The tool is positioned as a solution for teams seeking to secure AI usage, enforce compliance, and maintain oversight without disrupting productivity.
Patchguard is an AI-driven supply chain security platform designed to identify and remediate vulnerabilities across dependencies, containers, codebases, and related assets. The platform focuses on proactively detecting attack chains before they can be exploited, offering users a streamlined process for uncovering and fixing security issues in their software supply chain. A core feature of Patchguard is its free deterministic scan, which conducts a 30-second health check for any site without requiring signup. This scan performs 135 checks and is aligned with Mozilla Observatory standards, providing achievement badges based on results. For more advanced needs, Patchguard offers a Pro URL Scan that simulates live-site penetration testing, leveraging AI to analyze exploit chains and probe technologies such as NextAuth, GraphQL, and OAuth. Only verified findings are reported, ensuring actionable results. The platform also includes a Pro Repo Scan, which supports both quick scans for daily pull requests and deep audits for larger Java and Go repositories or compliance requirements. This scan maps findings to git blame, CWE, and CVE, and supports 25 programming languages. Patchguard’s AI Repair engine is designed to automatically generate and apply verified patches for detected vulnerabilities. The repair process follows a five-stage pipeline, including sandbox verification and re-scanning to ensure the effectiveness of each fix. The platform claims an average resolution time of ten seconds from detection to a verified pull request. Notable examples of detected issues include bypasses of web application firewalls via SPF leaks, exposure of internal API schemas through GraphQL introspection, and discovery of live API keys in public HTML sources. The platform can be used without signup for its free scan, while advanced features such as Pro URL Scan, Pro Repo Scan, and AI Repair are offered as part of paid plans. , and supports integrations with repositories from GitHub, npm, PyPI, Maven, Cargo, and Go modules. The service is positioned as an AI-native solution for supply chain security across a wide range of programming languages and environments.
Promptmonitor provides a dashboard for tracking how often AI platforms like ChatGPT, Claude, Gemini, and Perplexity mention your brand. It analyzes sources cited by AIs, monitors AI bot visits to your website, and offers GDPR-compliant analytics. Marketing teams can use it to improve brand visibility in AI-generated content and optimize outreach strategies.
PromptShield is a real-time API designed to protect large language model (LLM) applications from prompt injection attacks. It analyzes every user input and blocks malicious prompts before they reach the LLM, aiming to prevent exploits such as jailbreaks, system prompt leaks, and adversarial manipulations. The service targets developers and teams building AI-powered systems that require robust security against a wide range of prompt-based threats. The platform detects and blocks over 12 attack vectors, including jailbreaks (such as DAN, AIM, Developer Mode, and hundreds of known templates), prompt extraction attempts, role hijacking, indirect injection from external content, context manipulation, and data exfiltration. For each input, PromptShield provides a verdict (BLOCKED, SUSPICIOUS, or SAFE), a risk score, an explanation, and recommendations, all with an average latency under 200 milliseconds. The API can be integrated with a single HTTP request, and a Python SDK is available for streamlined setup, allowing developers to check if user messages are safe or obtain detailed scan results for further analysis and logging. PromptShield is delivered as a cloud-based REST API, with integration requiring only an API key and minimal setup. The service offers a live demo for real-time prompt analysis without signup and provides Swagger documentation for developers. Audit logs, custom rule sets, real-time alerts via webhooks, and dedicated support are available on higher-tier plans. For enterprises with strict compliance or deployment requirements, on-premise options, SOC 2 readiness, custom ML model tuning, and white-labeling are offered. Pricing includes a free tier with 50 API calls per month for developers and side projects, a Pro plan at $99 per month with 25,000 calls, a Business plan at $499 per month with 500,000 calls, and custom enterprise solutions with unlimited usage and additional compliance features. No credit card or forms are required to access the free tier, and users can obtain an API key instantly with just an email address.
Sentinel is a security platform designed to protect AI agents from prompt injection attacks and secret leaks before they reach large language models (LLMs). It addresses vulnerabilities in AI agents that process external content, where attackers may embed hidden instructions or attempt to bypass filters using encoding or fragmented attacks. Sentinel provides a multi-layered defense system specifically tailored to the challenges faced by AI agents operating in production environments. The platform incorporates four core layers of defense: content scanning, runtime detection, secret scanning, and continuously updated threat intelligence. Content scanning examines incoming data for hidden HTML, encoded payloads, instruction patterns, and fragmented attacks before they reach the LLM. Runtime detection monitors agent behavior during execution, identifying abnormal output patterns, privilege escalation attempts, and context hijacking. Secret scanning inspects outbound agent content in real time to prevent accidental exposure of API keys, tokens, AWS credentials, database URIs, and private keys. The system’s threat intelligence is continuously updated by a dedicated security team, ensuring new detection rules are shipped with every release to counter emerging attack techniques. Sentinel supports multi-format scanning, detecting threats in HTML, Markdown, JSON, plain text, and various encoded formats such as base64 and hex. It features evasion-resistant capabilities, including detection of developer mode jailbreaks, leetspeak obfuscation, and filler word insertion attacks. The tool is optimized for sub-second detection speeds suitable for production use, and maintains a block history log for all intercepted threats. Sentinel includes a system prompt auditor that assesses agent prompts for injection vulnerabilities and provides structured risk reports with actionable recommendations. Integration with popular AI agent frameworks is facilitated through middleware adapters for LangChain, CrewAI, Haystack, and AutoGen/AG2, allowing users to add Sentinel’s protection with minimal code changes. The platform runs locally on the user’s infrastructure, ensuring that data such as prompts, documents, and agent conversations never leave the machine. Sentinel is available with self-serve pricing starting at £5 per month, and detection rules are delivered encrypted and signed, auto-refreshed in the background to maintain up-to-date protection.
WrapSec is an AI security gateway designed to protect AI-powered applications from prompt injection, data leakage, and unsafe outputs before these issues can impact large language models (LLMs). Targeted at teams deploying AI in production environments, it provides an enforcement layer that operates between user input and the model, ensuring that crafted prompts cannot manipulate system instructions or expose sensitive data. The platform is intended for security teams and developers who require real-time policy enforcement and comprehensive audit trails for compliance and auditability. The tool features a multi-layer threat detection pipeline that combines rule-based detection, machine learning classification, and LLM semantic analysis. This approach covers both established attack patterns and emerging threats, aiming to catch issues that single-method systems might miss. WrapSec detects six main threat categories: prompt injection, jailbreak attempts, PII leakage, toxic content, data exfiltration, and malicious intent. It enforces protection on both input and output, identifying and redacting 22 types of personally identifiable information, and provides a full audit trail for every request and decision. WrapSec can be deployed on a team's own infrastructure within minutes and offers two integration modes: Scan-Only, which requires minimal changes and returns structured decisions (allow, block, sanitize) for forwarded prompts, and Proxy Mode, which acts as an OpenAI-compatible drop-in proxy that handles LLM requests end-to-end. In Proxy Mode, provider keys are stored encrypted and never exposed to the application, and the platform enforces policy on both incoming prompts and outgoing responses. The detection pipeline is designed for low latency, with rule detectors and PII guards operating in under a millisecond and optional transformer-based analysis available for more thorough inspection. The platform emphasizes a guardrail-first, fail-safe design, where any detector failure results in a blocked request rather than a silent pass. It also supports risk scoring, decision headers, and SIEM-ready audit exports. WrapSec is positioned as a solution for organizations that need enforcement and visibility across any LLM provider or self-hosted model, addressing limitations found in provider moderation tools and DIY filters.
AgentGuard is a free and open-source local desktop application designed to provide guardrails for AI coding agents. The tool focuses on enhancing security and efficiency by controlling and monitoring prompts and requests made by AI agents. Its primary features are Guardian Agent, which offers data loss prevention on prompts, tool inputs, and file reads, and Token Saver, which compresses verbose outputs and reduces unnecessary token usage before requests are sent to the AI model. Guardian Agent intercepts requests to block secrets, risky dependency installs, and oversized requests, applying token caps and flagging vulnerabilities in dependencies. It also provides update advice for outdated dependency pins. Token Saver reduces the context size by compressing shell outputs, caching repeated file reads, and shrinking noisy responses from search, diff, or JSON operations. These optimizations are tracked, with logs and analytics available to review token savings and event histories. AgentGuard includes review surfaces such as Logs, Analytics, and Garden. Logs provide a compact, exportable event history detailing Guardian and Token Saver actions. Analytics offer charts that track models used, token totals, savings, and trends in latency and tool calls. The Garden feature visualizes project activity, mapping modules, files, symbols, and import relationships. The application supports integration with three AI coding agents: Claude Code, Codex CLI, and Cursor. Guardian Agent's controls extend across all three integrations, while Token Saver offers the most extensive support for Claude Code. Delivery options include downloadable versions for Mac and Ubuntu, with the option to build from source using npm and Tauri for other operating systems. AgentGuard is positioned as a tool for developers seeking local data loss prevention, dependency protection, token optimization, and observability for workflows involving AI coding agents.
PsiGuard is a structural monitoring tool designed to observe AI-generated outputs in real time, focusing on how an AI model's answers are constructed as they are written. It addresses the challenge that AI systems, such as chatbots, agents, or voice AIs, often fail to recognize when their reasoning goes astray, typically leaving users to discover issues after the fact. Instead of fact-checking, PsiGuard monitors the coherence and structure of responses mid-sentence, providing signals when an answer may be drifting or breaking down. The platform offers an instant API key for quick integration, allowing users to start monitoring with minimal setup. PsiGuard supports connections to models from providers including OpenAI, Anthropic, Gemini, DeepSeek, and Grok by letting users paste their own API keys, which are stored encrypted. The tool provides a dashboard where users can watch the structural integrity of model outputs in real time, with readings such as coherence, drift, entropy, and memory coupling. PsiGuard can nudge a model's output back on course during a response, and logs every reading for review. PsiGuard is accessible via an SDK, installable through Python's pip or npm, and offers a quickstart guide and full documentation. The dashboard and monitoring features are available during a public beta period, which is currently free to use. Users can create a free account to manage API keys, increase usage caps, and retain their monitoring setups. The service positions itself as a structural monitor for AI outputs, providing early signals to investigate further, rather than offering definitive correctness.
